Long short-term memory (LSTM) is one of the robust recurrent neural netw...
While residual networks (ResNets) demonstrate outstanding performance on...
Over the past decade, deep hypercomplex-inspired networks have enhanced
...
Recently, many deep networks have introduced hypercomplex and related
ca...
Hearing-impaired is the disability of partial or total hearing loss that...
Long short-term memory (LSTM) is a robust recurrent neural network
archi...
This paper introduces a novel modification to axial-attention networks t...
Blood glucose (BG) management is crucial for type-1 diabetes patients
re...
We show that the core reasons that complex and hypercomplex valued neura...
Hybrid LSTM-fully convolutional networks (LSTM-FCN) for time series
clas...
Spatiotemporal sequence prediction is an important problem in deep learn...
Deep learning approaches have shown remarkable performance in many areas...
The problem of training spiking neural networks (SNNs) is a necessary
pr...
Hierarchical feature discovery using non-spiking convolutional neural
ne...
The final version of this paper has been published in IEEEXplore availab...
It is of some interest to understand how statistically based mechanisms ...
Spiking neural networks (SNNs) with adaptive synapses reflect core prope...